Stander Symposium Projects

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  Changes in a western Ohio old-growth forest community before and after invasion by emerald ash borer

  Julia I Chapman, Mitchell John Kukla, Corey Michael Kuminecz

  The emerald ash borer (EAB; Agrilus planipennis fairmaire) is an invasive insect species in North America that has devastated Fraxinus (ash) populations in the Great Lakes region and northeastern U.S.. Many forests are losing a significant number of Fraxinus trees and the implications of this widespread disturbance is not yet clear. The aim of this study is to understand how EAB-related tree mortality is impacting compositional change in a west central Ohio old-growth forest. A set of 32 nested plots were established in Drew Woods State Nature Preserve in 2011 and used to sample the overstory layer (314 m2; stems ≥ 2.5 cm diameter at breast height), sapling layer (10 m2; stems < 2.5 cm dbh and > 50 cm in height), and seedling layer (1 m2; stems < 50 cm in height). These plots were resampled in 2017 to investigate the composition of tree species over seven years during which the majority of Fraxinus trees died from EAB infestation. In the overstory, basal area of live Fraxinus decreased from 151.4 m2 ha-1 in 2011 to 1.68 m2 ha-1 in 2017. The basal area of dead Fraxinus increased from 33.5 m2 ha-1 in 2011 and to 132.3 m2 ha-1 in 2017. Further analysis will investigate how the relative abundance and stem density of tree species other than Fraxinus have changed during this time period. These findings can provide insight into the future successional trajectory of forests that have been infested with emerald ash borer.

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  Changes in Herbaceous Plant Diversity in an Old-Growth Ohio Forest Before and After Emerald Ash Borer Invasion

  Taylor Melissa Buskey

  The herbaceous layer of eastern North American deciduous forests is an important contributor to biodiversity in this region. One of the greatest threats to herbaceous plant diversity is the introduction of invasive species, which can suppress native species and alter local environmental conditions. Agrilus planipennis (emerald ash borer) is a non-native insect pest that has caused a mass death of ash trees (Fraxinus spp.) in North America since its introduction to the United States. The resultant changes in canopy structure may affect local conditions and thus have indirect impacts on herbaceous layer composition. Drew Woods State Nature Preserve is a 6-ha old-growth forest fragment in Darke County, Ohio that has recently experienced EAB-related ash mortality. Our goal was to understand how herbaceous layer diversity has been changing through time in response to this sitewide canopy disturbance. Annual surveys of herbaceous biodiversity were conducted across 32 1-m2 sampling plots from 2012 to 2017. Species richness, total cover, Shannon Diversity, and species evenness were calculated for each plot by year, and beta diversity (Bray-Curtis Dissimilarity) was used to assess community turnover through time. Repeated measures ANOVA was used to test for significant changes over this period, and regression analyses were used to understand relationships between diversity and environmental variables (canopy cover, soil moisture, and distance to forest edge). Species richness and herbaceous cover tended to be higher in more recent sampling years. There was a temporally consistent north-south gradient where diversity tended to be greater toward the southern edge of the stand. These results suggest that EAB-induced ash mortality is increasing light availability via canopy gap formation, which is a driving factor of herbaceous diversity. The full impact of EAB is not yet clear, but will likely extend beyond ash mortality and have important indirect effects on other parts of forest ecosystems.

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  Characterization of the Glycosylation of Aquaglyceroporin HC-3 in Erythrocytes from the Freeze Tolerant Anuran, Dryophytes chrysoscelis

  Dante Laurenti Pezzutti

  Cope’s gray treefrog, Dryophytes chrysoscelis, is a freeze-tolerant anuran that uses glycerol as a cryoprotectant. In erythrocytes of D. chrysoscelis, transmembrane glycerol flux is likely facilitated through the aquaglyceroporin, HC-3. Previous research demonstrated that erythrocytes from cold-acclimated treefrogs up-regulate HC-3 protein expression, membrane localization, and glycosylation. Thus, we hypothesize that anticipatory glycerol accumulation observed in cold-acclimated treefrogs contributes to enhanced post-translational modification of HC-3 via N-linked and O-linked glycosylation, and that HC-3 glycosylation is important in subcellular trafficking of HC-3 to the membrane. Densitometric analyses of immunoblots specific for HC-3 showed a 3.5-fold and 1.9-fold average increase in glycosylated HC-3 from RBCs cultured with the addition of glycerol (CCCM+G) as compared to Freshly Isolated RBCs (FI) and RBCs cultured in CCCM alone, respectively. Western blots of RBC proteins treated with PNGase F resulted in a 1.3-fold average decrease in glycosylated HC-3 compared to control proteins. However, protein treatment with O-Glycosidase and Neuraminidase did not change the abundance of glycosylated HC-3. Additional results were collected using scanning laser confocal microscopy and HC-3 localization was measured in mean fluorescent intensity (arbitrary units) using ImageJ software (N=4-6 cells per experiment). For RBCs cultured in CCCM+G, immunofluorescence intensity of HC-3 in the plasma membrane was 21.7 times greater than HC-3 immunofluorescence in the cytosol (P<0.05). In contrast, immunofluorescence intensity of HC-3 in the cytosol was 3.2 times greater than HC-3 immunofluorescence in the membrane for FI RBCs (P<0.01). Through the use of an in vitro cell culture system, we have recapitulated cold-acclimated in vivo HC-3 expression patterns through the addition of a glycerol-induced hyperosmotic environment to warm-acclimated erythrocyte cell cultures of D. chrysoscelis. Thus, in addition to its osmoregulatory role, glycerol may also influence the N-linked glycosylation and membrane trafficking of HC-3.

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  Characterization of Zinc-Histidine Interactions in Nvjp-1

  Brittanie M Rooths

  The mandible of Nereis virens, a marine sandworm, is mostly organic with stiffness and hardness comparable to that of human dentin. Nvjp-1 is the primary protein in the Nereis jaw and is inherently Histidine rich. Histidine contributes to the stability of the protein structure and superior mechanical properties through metal-coordinate bonds. Crosslinking of purified recombinant Nvjp-1 creates a water stable hydrogel that is capable of expanding and contracting upon exposure to various ions. Nvjp-1 hydrogels exhibit sclerotization through metal-coordination with divalent cations. Over ninety percent of the amino acid sequence of the carboxy-terminal of Nvjp-1 is comprised of only four amino acids. In order to determine the genetic/protein motifs directly responsible for the mechanical response, a carboxy-terminal truncation mutant of Nvjp-1 was recombinately expressed and crosslinked to form hydrogels. Dynamic mechanical analysis was performed on the carboxy-terminal truncation mutant to compare its mechanical properties to that of the full-length protein. De Novo structure prediction was performed using Molecular Dynamics simulations as a technique for determining native protein structures. The role of Zn-Histidine interactions in Nvjp-1 and their effect on protein structure was also investigated.

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  Chronic administration of probiotic L. rhamnosus increases anxiety-like behavior in group-housed male Long Evans rats

  Parker Maddison Griff

  Early life stress is a risk factor for later development of alcohol use disorders and anxiety disorders in humans. Using rodent experimental models, we know that rats experiencing social isolation as early-life stress exhibit greater anxiety-like behavior and alcohol consumption than rats housed in groups. Examining potential preventive strategies, we investigated the effects of probiotics, which have previously been shown to decrease rodent anxiety-like behavior, on the relationship between early-life stress and anxiety-like behavior in rats. We hypothesized that probiotics consumption would decrease anxiety-like behavior in socially isolated rats, as well as in rats housed in groups. To our surprise, we found that the probiotics had no significant effect on anxiety-like behavior for socially isolated rats but significantly increased anxiety-like behavior in rats housed in groups. Our results suggest probiotics do not have a positive benefit to alleviate consequences of early life stress and raise caution for their therapeutic use.

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  Climatic controls on the stable isotopic composition of precipitation in Ethiopia

  Colin McTighe

  This project aims to determine what major climatic factors control the variation of the stable isotopic composition of precipitation in Ethiopia. In the past, the variations of stable isotopes of precipitation have been linked to the North-South migration of the Intertropical convergence zone (ITCZ). However, recent studies suggested that the link between the ITCZ and the arrival of rainy seasons in Ethiopia do not provide enough explanation for the precipitation isotope values. In this study we examine the stable isotope values of precipitation for four stations throughout Ethiopia from August 2012 – August 2013, and determine how they are affected by a variety of climate factors including: local temperature and precipitation amount, sources of moisture (established through HYSPLIT modeling), convective intensity of moisture source region (estimated by the Outgoing Longwave Radiation (OLR)), wind circulation patterns, and moisture flux and transport. Our results will provide more insight to the control of precipitation isotopes in the tropical region, which is important for accurate interpretation of climate proxy data.

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  Cluster Computing with the Raspberry PI

  Ali Hussain Alwahimed

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  Combating Antibiotic Resistance in Multidrug Resistant Bacterial Cells using Plant Derived Inhibitory Compounds

  Emily Marie Jones

  Bacteria have steadily developed defenses against antibiotics since the world’s first fleet of antibacterial drugs was introduced. One strategy that bacteria can use to become multi-drug resistant involves the use of large, membrane-embedded efflux pumps, such as the AcrAB-TolC pump found in Escherichia coli (E. coli) and other Gram-negative bacteria cells. The most antibiotic-resistant cells are those which over-express the genes that code for this large efflux pump, and this gives the bacterium the capability of transporting a wide variety of compounds out of the cell, including antibiotics that we use to combat bacterial infections. The overexpression of these bacterial efflux pumps renders our antibiotics ineffective. To combat this antibiotic-resistance strategy, I will be analyzing plant extracts to identify new compounds that can block the activity of bacterial efflux pumps and restore the effectiveness of existing antibiotics. Fourteen roots, shoots, fruits, seeds, and leaves will be tested using a fluorescence-based efflux assay and any extracts that show inhibitory activity will be analyzed so that the active compound can be identified. This research could open up a new avenue in the treatment of multi-drug resistant bacterial infections.

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  Combinatorial Effects of Silver Nanoparticles and Hypoxia on Lung Cells

  Cameron Mark-Allan Crasto

  Silver nanoparticles are used in a variety of both consumer and medical applications. They possess antimicrobial properties that can stress mammalian cells through the formation of reactive oxygen species (ROS). This experiment looked at A549 human lung alveolar cells with exposure to 10nm silver citrate nanoparticles (AgNPs) in both a normal oxygen environment and hypoxic environment. Cell viability, formation of ROS, as well as the phosphorylation of both HSP27 and NFκB. In both environments, concentrations of 5µg/ml saw significant reduction in cell viability. There was a slight loss in cell viability in the hypoxic environment. The hypoxic environment saw significant increases in ROS at concentrations as low as 0.1µg/ml. In addition, when exposed to 5µg/ml of AgNPs, it was shown to increase phosphorylation of the HSP27, but reduce the phosphorylation of NFκB proteins, which play a crucial role in the stress level of a cell. (We are going to execute another experiment this week, which would combine exposure to AgNPs and low O2 - 10% CO2 on the A549 cell line. Once we get this data, we will update the abstract and be ready for the presentation.)

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  Community Shift Towards Individualism

  Hannah Katherine Donovan

  Public Social Capital is the network of relationships of people that a person knows and the resources they provide for them; as defined by McNamee (2014), “the social capital grapevine is only available in and through relationships and the groups which these relationships occur,” (79). The resource base for higher socioeconomic groups is far wider and deeper than that of those lower socioeconomic origins which creates a gap in information and influence between economic groups. Drawing on social inequality literature and the Facing Project Narratives related to public social capital, this poster will discuss the impact of changing neighborhoods and public social capital in the Dayton area. Understanding how social capital functions to either aid or limit in number of opportunities, resources, and connections in society. Currently and looking into the future, I hope to examine the resources available to connect people and grow in their associational life.

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  Compartmentalization and Temporal Distribution of L-DOPA-Containing Proteins Involved in Oyster Shell Formation

  Benjamin Nicholas Schmeusser

  Marine molluscs, such as Crassostrea virginica (eastern oyster), produce structural proteins that are essential in adhesive strategies and shell biomineralization. The unique properties of these proteins derive from the amino acid composition. L-3,4-dihydroxyphenylalanine (L-dopa), which is a unique key amino acid in the cross-linking of these proteins, can be considered a biomarker for identification and localization of shell formation proteins. The focus of this research was to determine the compartmentalization of L-dopa-containing proteins involved in the process of biomineralization in C. virginica at different time points during a shell repair event. Three organismal compartments were identified as possible locations of L-dopa precursor proteins: hemocytes, cell-free hemolymph, and mantle tissue. Hemolymph was harvested from the adductor muscle of notched oysters and hemocytes were subsequently collected via hemolymph centrifugation. Mantle tissue was collected from specific locations. The product of repair, nascent shell deposited in the notch, was collected at discrete time points post-notching. Amino acid composition related to time since notching was determined via anion exchange HPLC with pulsed amperometric detection. Additionally, the Arnow Assay (specific for catechols) was used to stain for L-dopa in the samples. Preliminary data reveal increased L-dopa concentrations in hemocytes and hemolymph at 24-48 hours and 96 hours post notching, respectively, indicating a mobilization of resources for shell repair. These data support the hypothesis that L-dopa-containing proteins are involved in oyster shell formation and that they are distributed at discrete locations within the organism.

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  Complications of Housing Arrangements in Dayton

  Dylan Anthony Penna-Powell

  American homeowners accumulate material wealth as they gain equity on their homes. A sociological look at how people are distributed around the city of Dayton according to their socioeconomic backgrounds reveals more than geographical details of social and economic inequality. This presentation explores the effects that disparities in housing arrangements have on closely related areas of interest such as education, access to affordable and nutritious foods, and individuals' likelihood of economic mobility. In addition, opportunities for reform through public education funding via local property tax dollars will be discussed. Reformation of a system in which the value of one's home is tightly linked to the quality of nearby public schools would provide greater opportunity for social and economic mobility to those in low-income communities.

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  Contrasting Patterns of Small and Large Glacial Lake Evolution in the Nepal Himalayas

  Katherine A Strattman

  The objective of this research is to assess annual ice velocities of three Himalayan glaciers in the Mount Everest region of Nepal. Glaciers worldwide are important indicators of climate change due to their tendencies of attaining equilibrium under changing climatic conditions. Imja, Lower Barun, and Hongu glaciers and their respective proglacial lakes have responded by retreat and growth, but at varying rates. Imja and Lower Barun Lakes have grown rapidly, but Hongu Glacier Lake has shown relatively slower growth. Despite the little accelerating growth of Hongu Glacier Lake, the moraine is composed of unconsolidated and unstable material, and poses the threat of an outburst flood due to less freeboard area. Therefore, it is important to monitor the development of all three lakes, as well as consider fluctuations of surface velocity. Using Landsat satellite imagery, I assessed the annual changes in surface ice velocity from 1992 to 2017. The yearly images were used as inputs to COSI-Corr, a co-registration and sub-pixel correlation software, to track changes on the glaciers surface. My results indicate short-term variations, despite all three glaciers’ location within the Mount Everest region, as well as similar long-term trends. Specifically, Imja, Lower Barun, and Hongu glaciers have shown long term trends of deceasing surface velocity, with varying rates of flow within each yearly pair. The three proglacial lakes have all grown at different rates as well, with Imja showing very rapid growth since the 1960s, Lower Barun showing deaccelerating growth, and Hongu showing very little growth. Understanding the dynamic nature of surface velocity can provide insight on overall glacier health, and may reveal how glaciers respond under rapid lake growth.

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  Convolutional Neural Network Based Multi-view Object Classification

  Zhiyuan Xie

  In recent years, neural networks have become more and more popular because of their outstanding performance in the object classification area. The convolutional neural network (CNN) is a deep learning, feed-forward neural network that has excellent performance in visual imagery analysis area. The idea of the connectivity pattern between neurons of the CNN came from the organization of the animal visual cortex. For human vision, different observational directions of objects can get different views. Human can easily recognize objects in different observational directions, but machines cannot achieve this easily. Therefore, multi-view object classification has been researched for many years. To solve this problem, we design an efficient CNN architecture to perform classification of the multi-view images of objects by appropriately choosing the number of layers, the sequence of layers cascading, and size of the filters. Then, we improve the classification performance by adding image enhancement techniques before CNN as a preprocessing stage. CNN extracts various significant features of the image. It is expected that an enhanced image helps to extract stronger features. The training and testing input images of the CNN are original images or enhanced images. The image enhancement is performed by nonlinear enhancement techniques such as multilevel windowed inverse sigmoid (MWIS) function based technique or a locally tuned sine nonlinearity (LTSN) technique. It is observed that the preprocessing by image enhancement provides improved performance in the cases of the smaller training set. Research work is in progress to modify the CNN architecture to see the impact of recognition performance for multi-view object classification. Advanced non-linear enhancement technologies might also be investigated to see the effectiveness in classification.

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  Cracking the Shell: An Investigation of Shell Repair in the Oyster, Crassostrea virginica

  Alyssa Ashley Outhwaite

  Mollusc shell formation has been an intriguing phenomenon for decades and current research efforts represent a paradigm shift in how oyster shell formation occurs. The older model of shell formation suggests a lack of cellular components as transport vectors for organic and mineral components. However, current research focuses on the potential role of oyster blood cells, hemocytes, in moving organic and mineral components to the shell formation front. A protein biomarker, the amino acid L-3,4-dihydroxyphenylalanine (L-DOPA), is unique to the proteins involved in insoluble organic matrix formation. Tracking the location and temporal occurrence of L-DOPA-containing proteins reveals the potential role of cells in shell repair. Three notch-repair experiments were conducted: a short term 36-hour notch-repair study, a mid-term 7-day notch-repair study, and a long term 8-week notch-repair study. At discrete time intervals, selected oyster compartments of hemocytes, mantle tissues, hemolymph, and nascent shell were sampled to determine the spatial and temporal distributions of the DOPA biomarker. Preliminary results show an increase in DOPA concentration in hemolymph from 0 to 48 hours. Conversely, hemocytes show a decrease in DOPA over time, with the greatest amount of DOPA present at 0 hours and a subsequent decrease over the course of repair. Additionally, nascent shell was analyzed during the 8-week study through the use of scanning electron microscopy (SEM). Analysis of the shell surface showed haphazard crystal formation under normal mineral deposition with crystals irregular in size, shape, and general placement. Newly formed shell from a notched specimen at 48 and 96 hours after notching; however, is characterized by directional and more uniformly shaped crystals. Together these results suggest that hemocytes are selectively shuttling and releasing protein resources to areas of shell repair and provide additional support for the cellular mediated shell formation model, where hemocytes play an active role in materials transport.

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  Creating a More Effective Explanation of Concussions for Intensive English Program Students

  Taylor Morgan Balk, Mark D Bugada, Caroline A Lynch, Olivia Marie Stanforth

  Low health literacy is a huge obstacle in communicating medical conditions and information to patients. An additional obstacle is created when physicians are communicating with international patients whose primary language is not English. The purpose of this project was to present written information on concussions to international students in the Level 2 Intensive English Program (IEP) at the University of Dayton in a format that they could read comfortably. For our methods, we went into the IEP classroom to assess the students’ knowledge of concussions. We then used the information the students provided along with an original fact sheet produced by the Center for Disease Control to create a brochure that would help the IEP students better understand concussions. We altered the original document’s wording, format, and content in order to display the information to the students so that they could better understand the material. Our document focused specifically on what a concussion is, its symptoms, and recovery tips. This final brochure corresponded with the IEP students’ reading level and allowed them to comprehend the information more clearly.

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  Cross Cultural Connections: A Phenomenological Study of Intercultural Learning from Intercultural Living.

  Megan Jacoby Woolf

  Higher education administrators and student affairs staff on some residential campuses have attempted to be more inclusive of international students and their U.S. peers by creating co-curricular learning communities addressing intercultural living. Intercultural residential communities, like Cross Cultural Connections (CCC) at the University of Dayton, serve to support the transition to intercultural living for first-year students. Through eight interviews of former CCC residents, this qualitative, phenomenological study explored how the community cultivates intercultural competence. According to the Refined Developmental Trajectory of Intercultural Maturity (Perez, Shim, King, & Baxter Magolda, 2015), former residents of the CCC expressed varying levels of advancements of their intercultural competence. This study assesses the longitudinal success of the CCC's learning outcomes and gives suggestions for similar intercultural residential communities.

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  Cross-Cultural Medical Interpretation: A Proposed Certificate for the University of Dayton

  Kevin Laurence Outwater

  The medical profession today is anchored with English as the primary language. Therefore, some individuals may struggle to communicate, causing the usage of interpreters to lower the burden for these patients. This interpretation model is going to address not only the primary skills of medical interpreters, but will also address languages and culture, in attempt to highlight meanings, and integrating other cultural notions. Since the demographics in the United States is changing, it is necessary to adapt these language and cultural changes to the medical field. Through this, I propose this interpretation model to be incorporated at the University of Dayton, becoming a medical interpretation certificate. This would follow the University’s belief in “Commitment to Community” by engaging with members of the Dayton area.

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  Crystallinity and Surface Morphology of Reactively Magnetron Sputtered Aluminum Scandium Nitride

  Rachel L Adams

  Aluminum nitride (AlN) is a low-loss piezoelectric that is commonly used in surface acoustic wave (SAW) and bulk acoustic wave (BAW) based filters for RF communication applications. It has previously been demonstrated that alloying AlN with scandium nitride (ScN) results in an increase of the piezoelectric coefficient up to five times greater than that of pure AlN without significantly increasing losses. This result could have significant impact on next-generation RF-filters. In order for this material to be incorporated into devices, a more thorough understanding of its growth, structural, electrical, and piezoelectric properties is needed. In this work, we investigate the role of deposition parameters during controllable-unbalanced reactive magnetron sputtering on the crystallinity, surface morphology, and composition of aluminum scandium nitride (AlxSc1-xN) on (0001)-oriented sapphire substrates. The conditions considered in this study include the sputter power, the nitrogen gas fraction, the gas ion flux to metal neutral flux ratio (ii/iMe) controlled by the coil current on an external electro-magnet, the substrate temperature, and the sputtering target Al-to-Sc ratio. X-ray photoelectron spectroscopy was used to determine the Al, Sc, and N concentrations in the films. X-ray diffraction of the films showed that the crystallinity was dependent upon ii/iMe and substrate temperature. The surface morphology, determined using atomic force microscopy, showed a similar dependence.

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  Data for our Students: How Three Large Public Universities Use Tech-Based Solutions to Foster and Track Student Success

  Ellen Elizabeth Marburger

  Using technological applications and databases for tracking student success in higher education is slowly becoming a necessity rather than a recommendation, especially at large campuses. This content analysis study sought to examine the breadth and depth of the use of these applications amongst three such universities in the midwest by analyzing and coding publicly available data around the themes of evaluation strategies, solutions, and communications. This study first examined the current commentary and research around this topic and defined student success indicators, identified three campuses, and finally compared the systems used, purposes for each, capabilities of each, and what gaps may still exist in the context of using such technology to assist in student success. Key findings suggest that this subset of the field is evolving, and widespread use and integration of these systems may be the next step for campuses and professionals, supplemented by future research.

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  Data Mining Approach for Estimating Residential Attic Thermal Resistance from Aerial Thermal Imagery, Utility Data, and Housing Data

  Salahaldin Faraj Alshatshati

  Conventional residential building energy auditing needed to identify opportunities for energy savings is expensive and time consuming. On-site energy audits require quantification of envelope U-values, air and duct leakage, and heating and cooling system efficiencies. There is a need to advance lower cost automated approaches, which could include aerial and drive-by thermal imaging at-scale in an effort to measure the building U-value. However, the thermal imaging approaches implemented to date, all based upon thermal-physical models of the envelopes, to estimate the U-values of walls require additional measurements and analysis prohibiting low-cost, at-scale implementation. This research focuses on interpreting aerial thermal images to estimate the U-value of roofs. A thermal-physics model of a ceiling is developed to show the difficulty in using the same approach used by others for walls, as new parameter estimates and thus more measurements would be required. A data-based methodology instead is posed. This approach integrates the inferred roof temperature measurement, historical utility data, and easily accessible or potentially easily accessible housing data. A Random Forest model is developed from a training subset of residences for which the ceiling U-values are known. This model is used to predict the roof U-values in a validation set of houses with unknown U-value. Demonstrated is an ability to estimate the attic/roof U-value with an R-squared value in the range of 0.96 using as few as 24 training houses. The implication of this research is significant, offering the possibility of auditing residences remotely at-scale via aerial and drive-by thermal imaging

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  Data Mining of Smart WiFi Thermostats to Develop Multiple Zonal Dynamic Energy and Comfort Models of a Residential Building

  Abdulrahman Mubarak Q Alanezi, Kefan Huang

  Smart WiFi thermostats have gained an increasing foothold in the residential building market. The data emerging from from these thermostats is transmitted to the cloud. Companies like Nest and Emerson Climate Technologies are attempting to use this data to add value to their customers. This overarching theme establishes the foundation for this research. This research seeks to utilize WiFi data from the Emerson Climate Technologies’ Helix test house to: develop a dynamic model to predict real time cooling demand and then apply this model to running ‘what-if’ thermostat scheduling scenarios with the ultimate goal of reducing energy use in the residence or responding to high demand events. The Helix residence, with two thermostat controlled zones for each floor, exists in a temperature/humidity controlled external environment, which can be controlled to simulate environmental conditions present in the hottest to coldest climates. A Design of Experiment approach was used to establish data needed for the model. The control variables in the experiments included: levels for the exterior environmental schedule and levels for the interior setpoint schedules for both zones. Simply, this data enabled data collection for constant or cyclical exterior environmental conditions and constant and scheduled interior setpoint conditions, not necessarily the same for each floor. From this data, a regression tree approach (Random Forest) was used to develop models to predict the room temperature as measured by each thermostat, as well as the cooling status for each zone. The models developed, when applied to validation data (e..g, data not employed in training the model) R2 values of greater than 0.95. Then, the models developed were utilized for various ‘What if’ scenarios. Two such scenarios were considered. The first looked at the possibility of using the model to estimate comfort in a demand response event, e.g., when the grid manager calls for demand reduction. In this case, the heat pump providing cooling would be powered off for some time. The second scenario sought to quantify the cooling savings from use of higher thermostat setpoint during simulated non-occupied periods and for different exterior temperature schedules. The ‘What if’ predictions are validated with experimental data, thus demonstrating the value of the data-driven, dynamic data solely from smart WiFi thermostat information.

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  Dayton and the Great Recession

  Nick Steven Lafrance

  Today, the city of Dayton, Ohio is still currently experiencing the side effects of the housing plummet in 2008, also known as the Great Recession. This poster will examine how, what, and why the Great Recession of 2008 happened. Meanwhile, keeping in mind that this is not the first time our country has experienced an economic fall. Drawing on social inequality literature, Facing Project Narratives, and national and local data, this poster will follow the effects the Great Recession has had on our local economy and more specifically the city of Dayton.

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  Dayton and the Opioid Epidemic: A Tragedy in the Making

  Courtney Rose Kemna

  Dayton has one of the highest drug overdose rates in the United States. This opioid epidemic can be linked to a number of broader socioeconomic challenges facing the area, including unemployment, the decline of manufacturing, and location. This poster will highlight information on this epidemic and its causes in the Dayton area. To do this, I will draw on social science concepts and theory as well as informal interviews with professionals who are engaged in the epidemic. In addition, I will provide an overview of current efforts in Dayton to address this issue (e.g. Community Overdose Action Team, Miracle Makers, and East End Community Services) and argue that long term solutions will require addressing the root causes of the epidemic.

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  Deep Neural Network Based on FPGA

  Shuo Zhang

  With the rapid proliferation of computing systems and the internet, the amount of data generated has been increasing exponentially. This includes data from mobile devices, where almost all information is now becoming computerized, and science experiments, where large simulations on supercomputers are increasingly becoming the norm. With this massive increase in data, a key issue is how we process and make sense of this data. This is called the “Big Data” challenge. Deep learning is a class of mathematical algorithms that is now heavily used for Big Data analytics. These algorithms are based on very large scale neural networks. One of the key challenges with deep learning is that it requires massive computing power. At present clusters of high performance graphics cards designed primarily for computing (known as GPGPUs) are used for these tasks. A key problem with clusters of GPGPUs, is that they consume large amounts of energy, thus making it difficult to scale existing massive computing systems to future Big Data volumes. The deep neural network designed by Parallel Cognitive Systems Laboratory is based on application specific integrated circuits (ASIC), which provides high performance at reasonably low power consumption. However, these are extremely expensive to fabricate. The Field Programmable Gate Array (FPGA) is a type of integrated circuit that can be reconfigured to implement a large range of arbitrary functions according to application requirements. FPGAs are much cheaper than ASIC and consume less power than CPU and GPU. The objective of this proposal is to develop deep learning network based on FPGA. I will optimize the whole design to make it more suitable for the deep learning. Several pattern recognition applications which use deep learning will be used to test and evaluate the design.